Automatic Power Line Inspection Using UAV Images

Zhang, Yong; Yuan, Xia; Li, Wenzhuo; Chen, Shiyu

doi:10.3390/rs9080824

Cited by 141 publications

(88 citation statements)

References 27 publications

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“…While the positioning and self-recovering problems have been addressed, the system was intended for semi-autonomous operations that would require an operator to instruct the UAV. To improve the level of autonomy, images obtained by UAVs can be used to detect inspecting objects and create paths for autonomous flights [22], [3].…”

Section: Related Workmentioning

confidence: 99%

System Architecture for Real-Time Surface Inspection Using Multiple UAVs

Hoang

Phung

Dinh

et al. 2020

IEEE Systems Journal

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This paper presents a real-time control system for surface inspection using multiple unmanned aerial vehicles (UAVs). The UAVs are coordinated in a specific formation to collect data of the inspecting objects. The communication platform for data transmission is based on the Internet of Things (IoT). In the proposed architecture, the UAV formation is established via using the angle-encoded particle swarm optimisation to generate an inspecting path and redistribute it to each UAV where communication links are embedded with an IoT board for network and data processing capabilities. Data collected are transmitted in real time through the network to remote computational units. To detect potential damage or defects, an online image processing technique is proposed and implemented based on histograms. Extensive simulation, experiments and comparisons have been conducted to verify the validity and performance of the proposed system.

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Section: Related Workmentioning

confidence: 99%

System Architecture for Real-Time Surface Inspection Using Multiple UAVs

Hoang

Phung

Dinh

et al. 2020

IEEE Systems Journal

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“…Luo et al [10] proposed an object-aware definition for power lines in joint RGB-NIR images to extract potential segments, followed by intensity features from NIR images to refine outputs. Zhang et al [11,12] applied a hand-designed filter to extract power line features, then adopted epipolar constraints to refine power line segments. Although this kind of approaches have achieved great improvements in recent years, the limitations are still obvious when applied to real environment.…”

Section: Related Workmentioning

confidence: 99%

Detecting Power Lines in UAV Images with Convolutional Features and Structured Constraints

Zhang

Yang

et al. 2019

Remote Sensing

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Power line detection plays an important role in an automated UAV-based electricity inspection system, which is crucial for real-time motion planning and navigation along power lines. Previous methods which adopt traditional filters and gradients may fail to capture complete power lines due to noisy backgrounds. To overcome this, we develop an accurate power line detection method using convolutional and structured features. Specifically, we first build a convolutional neural network to obtain hierarchical responses from each layer. Simultaneously, the rich feature maps are integrated to produce a fusion output, then we extract the structured information including length, width, orientation and area from the coarsest feature map. Finally, we combine the fusion output with structured information to get a result with clear background. The proposed method fully exploits multiscale and structured prior information to conduct both accurate and efficient detection. In addition, we release two power line datasets due to the scarcity in the public domain. The method is evaluated on the well-annotated power line datasets and achieves competitive performance compared with state-of-the-art methods.

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“…The status detection of electric power equipment is an essential technique for the high-voltage transmission lines inspection in which a wide variety of sensors are used [1]. Over the past few decades, vision sensor-based methods have been developed rapidly, and many topics have been examined, such as insulator detection [2], power line detection [3,4], and power tower detection [5,6]. Early studies show that the insulator string is one of the most important pieces of equipment of the high-voltage transmission line as it can provide both mechanical support and electrical insulation.…”

Section: Introductionmentioning

confidence: 99%

A Method of Insulator Faults Detection in Aerial Images for High-Voltage Transmission Lines Inspection

et al. 2019

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Insulator faults detection is an important task for high-voltage transmission line inspection. However, current methods often suffer from the lack of accuracy and robustness. Moreover, these methods can only detect one fault in the insulator string, but cannot detect a multi-fault. In this paper, a novel method is proposed for insulator one fault and multi-fault detection in UAV-based aerial images, the backgrounds of which usually contain much complex interference. The shapes of the insulators also vary obviously due to the changes in filming angle and distance. To reduce the impact of complex interference on insulator faults detection, we make full use of the deep neural network to distinguish between insulators and background interference. First of all, plenty of insulator aerial images with manually labelled ground-truth are collected to construct a standard insulator detection dataset ‘InST_detection’. Secondly, a new convolutional network is proposed to obtain accurate insulator string positions in the aerial image. Finally, a novel fault detection method is proposed that can detect both insulator one fault and multi-fault in aerial images. Experimental results on a large number of aerial images show that our proposed method is more effective and efficient than the state-of-the-art insulator fault detection methods.

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Automatic Power Line Inspection Using UAV Images

Cited by 141 publications

References 27 publications

System Architecture for Real-Time Surface Inspection Using Multiple UAVs

System Architecture for Real-Time Surface Inspection Using Multiple UAVs

Detecting Power Lines in UAV Images with Convolutional Features and Structured Constraints

A Method of Insulator Faults Detection in Aerial Images for High-Voltage Transmission Lines Inspection

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